# (Senior) Scientist AI/ML for Protein and Metabolic Engineering
Join dsm-firmenich's Computational Biotechnology team as a highly skilled AI/ML-focused data scientist, driving next-generation innovations in protein and metabolic engineering.
## Key Responsibilities
- Lead the application of AI and data science to accelerate high-impact protein and metabolic engineering across key business segments
- Develop and continuously improve advanced models for DNA, RNA, proteins, and metabolic pathways, integrating them into engineering workflows
- Translate complex modeling results into clear, actionable insights for teams, stakeholders, and customers
- Establish and promote best practices, standards, and scalable platforms within the global data and life sciences community
- Monitor emerging advances in computational biology and AI, driving adoption of innovative methods with strategic value
- Collaborate closely with cross-functional teams worldwide, applying modern ML and software engineering practices to deliver project success
## Requirements
- PhD (or equivalent) in Biochemistry, Biophysical Chemistry, Bioinformatics, Computer Science, or Artificial Intelligence, with focus on computational approaches to protein and strain engineering
- 3-7 years of academic or industry experience applying data- and knowledge-driven methods in protein and/or metabolic engineering
- Hands-on experience with foundation models in biology, including fine-tuning and applying sequence, structure-aware, generative, and pathway models to real-world challenges
- Strong expertise in deep learning with practical experience in architectures such as transformers, GNNs, and/or diffusion models, ideally incorporating biological priors
- Experience working with HPC environments and large-scale AI/ML workflows, including distributed computing and GPU-accelerated model training and deployment
- Proficiency in Python and modern ML practices, with strong problem-solving, collaboration, and communication skills
## What We Offer
- Dynamic and fast-growing team applying AI/ML and advanced modeling techniques to biotechnology
- Highly motivated, professional, multicultural, and interdisciplinary work environment
- Opportunity to apply scientific expertise to innovations in health, nutrition, and beauty
- Continuous learning and development through in-house training programs
- Company with strong legacy of industrial innovation and cutting-edge technology, with over 2,000 scientists and more than 700 million annual Science & Research investments